• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.1
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• pp.99-111
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• 2016

This paper presents an integrated fault diagnosis algorithm for driving motor of In-wheel independent drive electric vehicle. Especially, this paper proposes a method that integrated the high level fault diagnosis and the low level fault diagnosis in order to improve a robustness and performance of the fault diagnosis system. The high level fault diagnosis is performed using the vehicle dynamics analysis and the low level fault diagnosis is carried using the motor system analysis. The validity of the high level fault diagnosis algorithms was verified through $Carsim^{(R)}$ and MATLAB/$Simulink^{(R)}$ cosimulation and the low level fault diagnosis's validity was shown by applying it to a MATLAB/$Simulink^{(R)}$ interior permanent magnet synchronous motor control system. Finally, this paper presents a fault diagnosis strategy by combining the high level fault diagnosis and the low level fault diagnosis.

• Journal of Drive and Control
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• v.11 no.2
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• pp.16-21
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• 2014

The purpose of this paper is to construct a control algorithm for improving the driving efficiency of 4-wheel-drive in-wheel electric vehicles. The main parts of the vehicle were modeled and the input-output relations of signals were summarized using MATLAB/Simulink. A performance simulator for 4-wheel-drive in-wheel electric vehicles was developed based on the co-simulation environment with a commercial dynamic behavior analysis program called Carsim. Moreover, for improving the driving efficiency of vehicles, a torque distribution algorithm, which distributes the torque to the front and rear wheels, was included in the performance simulator. The effectiveness of the torque distribution algorithm was validated by the SOC simulation using the FTP-75 driving cycle.

• Journal of Drive and Control
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• v.16 no.3
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• pp.67-74
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• 2019

The automotive market has recently been investing much time and costs in improving existing technologies such as ABS (Anti-lock Braking System) and TCS (Traction Control System) and developing new technologies. Additionally, various methods have been applied and developed to reduce this. Among them, the development method using the simulation has been mainly used and developed. In this paper, we have studied a method to develop SILS (Software In the Loop Simulation) for TCS which can test various environment variables under the same conditions. We modeled hardware (vehicle engine and ABS module) and software (control logic) of TCS using MATLAB/Simulink and Carsim. Simulation was performed on the climate, road surface, driving course, etc. to verify the TCS logic. By using SILS to develop TCS control logic and controller, it is possible to verify before production and reduce the development period, manpower and investment costs.

• International Journal of Highway Engineering
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• v.13 no.2
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• pp.95-102
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• 2011

Anti-icing system can immediately respond when snowing is expected or the snow comes down on the road surface. It has been recognized that the system can reduce traffic accidents and congestion by quickly removing the frozen road surface area. However, it is very difficult to implement this system due to the expensive equipment installation and operation cost, Recently, there was a developed program for predicting the freezing area using three-dimensional model and tracking the sun path. But, there is no objective analysis method and all developed approaches are different so that the general standard of anti-icing system is needed. In this study, we proposed the decision criteria for determining application priorities of the anti-icing system based on weather and road conditions, i.e., geometric and topographic conditions. Regional climate survey, topographical analysis, and dynamic vehicle simulation considered road geometry and skid resistance was conducted to standardize the installation method of anti-icing system.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.208-214
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• 2014

Vehicle dynamic states used in various advanced driving safety systems are influenced by road geometry. Among the road geometry information, the vehicle pitch angle influenced by road slope and acceleration-deceleration is essential parameter used in pose estimation including the navigation system, advanced adaptive cruise control and others on sag road. Although the road slope data is essential parameter, the method measuring the parameter is not commercialized. The digital map including the road geometry data and high-precision DGPS system such as DGPS(Differential Global Positioning System) based RTK(Real-Time Kinematics) are used unusually. In this paper, low-cost cascade extended Kalman filter(CEKF) based road slope estimation method is proposed. It use cascade two EKFs. The EKFs use several measured vehicle states such as yaw rate, longitudinal acceleration, lateral acceleration and wheel speed of the rear tires and 3 D.O.F(Degree Of Freedom) vehicle dynamics model. The performance of proposed estimation algorithm is evaluated by simulation based on Carsim dynamics tool and T-car based experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1879-1885
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• 2017

This paper discusses the trajectory tracking system of unmanned ground vehicles based on predictive control. Because the unmanned ground vehicles can not satisfactorily complete the path tracking task, highly efficient and stable trajectory control system is necessary for unmanned ground vehicle to be realized intelligent and practical. According to the characteristics of unmanned vehicle, this paper built the kinematics tracking models firstly. Then studied algorithm solution with the tools of the optimal stability analysis method and proposed a tracking control method based on the model predictive control. The controller used a kinematics-based prediction model to calculate the predictive error. This controller helps the unmanned vehicle drive along the target trajectory quickly and accurately. The designed control strategy has the true robustness, simplicity as well as generality for kinematics model of the unmanned vehicle. Furthermore, the computer Simulink/Carsim results verified the validity of the proposed control method.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.44-49
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• 2013

This paper presents a lateral collision risk index between an ego vehicle and a rear-side vehicle. The lateral collision risk is designed to represent a lateral collision risk and provide the appropriate threshold value of activation of the lateral collision management system such as the Blind Spot Detection(BSD). The lateral collision risk index is designed using the Time to Line Crossing(TLC) and the longitudinal collision index at the predicted TLC. TLC and the longitudinal collision index are calculated with the signals from the exterior sensor such as the radar equipped on the rear-side of a vehicle and a vision sensor which detects the distance and time to the lane departure. For the robust situation assessment, the perception of driving environment determining whether the road is straighten or curved should be determined. The relative motion estimation method has been proposed with the road information via the integrated estimator using the environment sensors and vehicle sensor. A lateral collision risk index was composed with the estimated relative motion considering the relative yaw angle. The performance of the proposed lateral collision risk index is investigated via computer simulations conducted using the vehicle dynamics software CARSIM and Matlab/Simulink.